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Downwind Fire and Smoke Detection during a Controlled Burn—Analyzing the Feasibility and Robustness of Several Downwind Wildfire Sensing Modalities through Real World Applications

Year of Publication
2023
Publication Type

Wildfires have played an increasing role in wreaking havoc on communities, livelihoods, and ecosystems globally, often starting in remote regions and rapidly spreading into inhabited areas where they become difficult to suppress due to their size and unpredictability. In sparsely populated remote regions where freshly ignited fires can propagate unimpeded, the need for distributed fire detection capabilities has become increasingly urgent. In this work, we evaluate the potential of a multitude of different sensing modalities for integration into a distributed downwind fire detection system, something which does not exist today. We deployed custom sensor-rich data logging units over a multi-day-controlled burn event hosted by the Marin County Fire Department in Marin County, CA. Under the experimental conditions, nearly all sensing modalities exhibited signature behaviors of a nearby active fire, but with varying degrees of sensitivity. We present promising preliminary findings from these field tests but also note that future work is needed to assess more prosaic concerns. Larger scale trials will be needed to determine the practicality of specific sensing modalities in outdoor settings, and additional environmental data and testing will be needed to determine the sensor system lifetime, data delivery performance, and other technical considerations. Crucially, this work provides the preliminary justification underscoring that future work is potentially valuable and worth pursuit.

Authors
P. Chwalek; H. Chen; P. Dutta; J. Dimon; S. Singh; C. Chiang; T. Azwell
Citation

Chwalek P, Chen H, Dutta P, Dimon J, Singh S, Chiang C, Azwell T. Downwind Fire and Smoke Detection during a Controlled Burn—Analyzing the Feasibility and Robustness of Several Downwind Wildfire Sensing Modalities through Real World Applications. Fire [Internet]. 2023 ;6(9). Available from: https://www.mdpi.com/2571-6255/6/9/356

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